Transition to seizure in focal epilepsy: From <scp>SEEG</scp> phenomenology to underlying mechanisms

Auteurs

Kayabas MA, Köksal Ersöz E, Yochum M, Bartolomei F, Benquet P, Wendling F

Les auteurs en lien sont membres de l'INS.

Équipes

DynaMap

Résumé

Abstract Objective For the pre‐surgical evaluation of patients with drug‐resistant focal epilepsy, stereo‐electroencephalographic (SEEG) signals are routinely recorded to identify the epileptogenic zone network (EZN). This network consists of remote brain regions involved in seizure initiation. However, the pathophysiological mechanisms underlying typical SEEG patterns that occur during the transition from interictal to ictal activity in distant brain nodes of the EZN remain poorly understood. The primary aim is to identify and explain these mechanisms using a novel physiologically‐plausible model of the EZN. Methods We analyzed SEEG signals recorded from the EZN in 10 patients during the transition from interictal to ictal activity. This transition consisted of a sequence of periods during which SEEG signals from distant neocortical regions showed stereotypical patterns of activity: sustained preictal spiking activity preceding a fast activity occurring at seizure onset, followed by the ictal activity. Spectral content and non‐linear correlation of SEEG signals were analyzed. In addition, we developed a novel neuro‐inspired computational model consisting of bidirectionally coupled

Abstract Objective For the pre‐surgical evaluation of patients with drug‐resistant focal epilepsy, stereo‐electroencephalographic (SEEG) signals are routinely recorded to identify the epileptogenic zone network (EZN). This network consists of remote brain regions involved in seizure initiation. However, the pathophysiological mechanisms underlying typical SEEG patterns that occur during the transition from interictal to ictal activity in distant brain nodes of the EZN remain poorly understood. The primary aim is to identify and explain these mechanisms using a novel physiologically‐plausible model of the EZN. Methods We analyzed SEEG signals recorded from the EZN in 10 patients during the transition from interictal to ictal activity. This transition consisted of a sequence of periods during which SEEG signals from distant neocortical regions showed stereotypical patterns of activity: sustained preictal spiking activity preceding a fast activity occurring at seizure onset, followed by the ictal activity. Spectral content and non‐linear correlation of SEEG signals were analyzed. In addition, we developed a novel neuro‐inspired computational model consisting of bidirectionally coupled

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